An analysis method for time ordered data processing of Dark Matter experiments

The analysis of the time ordered data of Dark Matter experiments is becoming more and more challenging with the increase of sensitivity in the ongoing and forthcoming projects. Combined with the well-known level of background events, this leads to a rather high level of pile-up in the data. Ionization, scintillation as well as bolometric signals present common features in their acquisition timeline: low frequency baselines, random gaussian noise, parasitic noise and signal characterized by well-defined peaks. In particular, in the case of long-lasting signals such as bolometric ones, the pile-up of events may lead to an inaccurate reconstruction of the physical signal (misidentification as well as fake events). We present a general method to detect and extract signals in noisy data with a high pile-up rate and qe show that events from few keV to hundreds of keV can be reconstructed in time ordered data presenting a high pile-up rate. This method is based on an iterative detection and fitting procedure combined with prior wavelet-based denoising of the data and baseline subtraction. {We have tested this method on simulated data of the MACHe3 prototype experiment and shown that the iterative fitting procedure allows us to recover the lowest energy events, of the order of a few keV, in the presence of background signals from a few to hundreds of keV. Finally we applied this method to the recent MACHe3 data to successfully measure the spectrum of conversion electrons from Co57 source and also the spectrum of the background cosmic muons

Erosion: wins races by a landslide

This model demonstrates the effects of erosion on soil. Users are able to adjust both rain (water) and wind intensity as well as rates of erosion for both. There is also an option to add different amounts of vegetative land cover; allowing users to see how areas with land cover are not as susceptible to erosion as open areas. The lesson plan has students run multiple trials, record data, create graphs and lines of best fit. The line of best fit is than used to make predictions and estimations. This was designed as a supplement to an erosion lesson and does not include all factors that affect erosion

Project of a superfluid He3 detector for direct detection of non-baryonic dark matter : MACHe3

MACHe3 (MAtrix of Cells of superfluid Helium 3) is a project of non-baryonic Dark Matter search using superfluid He3 as sensitive medium. Simulations on a high granularity matrix show very good rejection against background events. First results on a prototype cell are very encouraging. Neutron detection has been highlighted as well as cosmic muon detection. A phenomenological study has been done with the DarkSUSY code to investigate complementarity of MACHe3 with existing Dark Matter detectors.Comment: 5 pages, 5 figures, to appear in Proceedings of the 4th Marseille International Cosmology Conferenc

Reflexion M\"ossbauer analysis of the in situ oxidation products hydroxycarbonate green rust

The purpose of this study is to determine the nature of the oxidation products of FeII-III hydroxycarbonate FeII4FeIII2(OH)12CO3~3H2O (green rust GR(CO32-)) by using the miniaturised M\"ossbauer spectrometer MIMOS II. Two M\"ossbauer measurements methods are used: method (i) with green rust pastes coated with glycerol and spread into Plexiglas sample holders, and method (ii) with green rust pastes in the same sample holders but introduced into a gas-tight cell with a beryllium window under a continuous nitrogen flow. Method (ii) allows us to follow the continuous deprotonation of GR(CO32-) into the fully ferric deprotonated form FeIII6O4(OH)8CO3~3H2O by adding the correct amount of H2O2, without any further oxidation or degradation of the samples

Equilibria in Sequential Allocation

Sequential allocation is a simple mechanism for sharing multiple indivisible items. We study strategic behavior in sequential allocation. In particular, we consider Nash dynamics, as well as the computation and Pareto optimality of pure equilibria, and Stackelberg strategies. We first demonstrate that, even for two agents, better responses can cycle. We then present a linear-time algorithm that returns a profile (which we call the "bluff profile") that is in pure Nash equilibrium. Interestingly, the outcome of the bluff profile is the same as that of the truthful profile and the profile is in pure Nash equilibrium for \emph{all} cardinal utilities consistent with the ordinal preferences. We show that the outcome of the bluff profile is Pareto optimal with respect to pairwise comparisons. In contrast, we show that an assignment may not be Pareto optimal with respect to pairwise comparisons even if it is a result of a preference profile that is in pure Nash equilibrium for all utilities consistent with ordinal preferences. Finally, we present a dynamic program to compute an optimal Stackelberg strategy for two agents, where the second agent has a constant number of distinct values for the items

Self-enforcing cooperation via strategic investment

We investigate how, in a situation with two players in which noncooperation is the only equilibrium, cooperation can be achieved via costly investment. We find that in the resulting equilibria, cooperation is an all-or-nothing outcome, that is, either there is full cooperation by both players, or no cooperation at all. The cost of investment is unrelated to the degree of cooperation that is ultimately achieved, unless the cost is too high, in which case investment cannot in any degree overcome the disincentive to cooperate. Moreover, the positive externalities that players have on each other in the course of play, although they affect investment, are ultimately irrelevant to the degree of cooperation achieved. We view our model as an explanation for the formation and stable existence of business alliances, where the players are firms forming a partnership defined and sustained by contractual agreements, but which is short of a merger or acquisition

MACHe3, a prototype for non-baryonic dark matter search: KeV event detection and multicell correlation

Superfluid He3 at ultra-low temperatures (100 microKelvins) is a sensitive medium for the bolometric detection of particles. MACHe3 (MAtrix of Cells of Helium 3) is a project for non-baryonic dark matter search using He3 as a sensitive medium. Simulations made on a high granularity detector show a very good rejection to background signals. A multicell prototype including 3 bolometers has been developed to allow correlations between the cells for background event discrimination. One of the cells contains a low activity Co57 source providing conversion electrons of 7.3 and 13.6 keV to confirm the detection of low energy events. First results on the multicell prototype are presented. A detection threshold of 1 keV has been achieved. The detection of low energy conversion electrons coming from the Co57 source is highlighted as well as the cosmic muon spectrum measurement. The possibility to reject background events by using the correlation among the cells is demonstrated from the simultaneous detection of muons in different cells